Developing constitutive models from EPR‐based self‐learning finite element analysis          下载免费PDF全文

Ali Nassr  Akbar Javadi  Asaad Faramarzi 《国际地质力学数值与分析法杂志》2018,42(3):401-417

A constitutive model that captures the material behavior under a wide range of loading conditions is essential for simulating complex boundary value problems. In recent years, some attempts have been made to develop constitutive models for finite element analysis using self‐learning simulation (SelfSim). Self‐learning simulation is an inverse analysis technique that extracts material behavior from some boundary measurements (eg, load and displacement). In the heart of the self‐learning framework is a neural network which is used to train and develop a constitutive model that represents the material behavior. It is generally known that neural networks suffer from a number of drawbacks. This paper utilizes evolutionary polynomial regression (EPR) in the framework of SelfSim within an automation process which is coded in Matlab environment. EPR is a hybrid data mining technique that uses a combination of a genetic algorithm and the least square method to search for mathematical equations to represent the behavior of a system. Two strategies of material modeling have been considered in the SelfSim‐based finite element analysis. These include a total stress‐strain strategy applied to analysis of a truss structure using synthetic measurement data and an incremental stress‐strain strategy applied to simulation of triaxial tests using experimental data. The results show that effective and accurate constitutive models can be developed from the proposed EPR‐based self‐learning finite element method. The EPR‐based self‐learning FEM can provide accurate predictions to engineering problems. The main advantages of using EPR over neural network are highlighted.  相似文献   

Modelling the effect of changing precipitation inputs on deep soil water utilization          下载免费PDF全文

Ji Qi  Daniel Markewitz  David Radcliffe 《水文研究》2018,32(5):672-686

Forests in the Southeastern United States are predicted to experience future changes in seasonal patterns of precipitation inputs as well as more variable precipitation events. These climate change‐induced alterations could increase drought and lower soil water availability. Drought could alter rooting patterns and increase the importance of deep roots that access subsurface water resources. To address plant response to drought in both deep rooting and soil water utilization as well as soil drainage, we utilize a throughfall reduction experiment in a loblolly pine plantation of the Southeastern United States to calibrate and validate a hydrological model. The model was accurately calibrated against field measured soil moisture data under ambient rainfall and validated using 30% throughfall reduction data. Using this model, we then tested these scenarios: (a) evenly reduced precipitation; (b) less precipitation in summer, more in winter; (c) same total amount of precipitation with less frequent but heavier storms; and (d) shallower rooting depth under the above 3 scenarios. When less precipitation was received, drainage decreased proportionally much faster than evapotranspiration implying plants will acquire water first to the detriment of drainage. When precipitation was reduced by more than 30%, plants relied on stored soil water to satisfy evapotranspiration suggesting 30% may be a threshold that if sustained over the long term would deplete plant available soil water. Under the third scenario, evapotranspiration and drainage decreased, whereas surface run‐off increased. Changes in root biomass measured before and 4 years after the throughfall reduction experiment were not detected among treatments. Model simulations, however, indicated gains in evapotranspiration with deeper roots under evenly reduced precipitation and seasonal precipitation redistribution scenarios but not when precipitation frequency was adjusted. Deep soil and deep rooting can provide an important buffer capacity when precipitation alone cannot satisfy the evapotranspirational demand of forests. How this buffering capacity will persist in the face of changing precipitation inputs, however, will depend less on seasonal redistribution than on the magnitude of reductions and changes in rainfall frequency.  相似文献   

深水铺管船托管架疲劳分析及动态监测点选取研究     

闫宏生  王哲  王晓波  陈永訢  孟祥伟 《海洋工程》2018,36(1):107-113

作为S型铺管作业的关键性装备,托管架长期承受着交变载荷的作用,随着海洋开发向超深水发展,结构疲劳破坏问题不容忽视。采用疲劳谱分析的方法并结合线性累积损伤理论,对托管架结构频域下的变形进行了分析,计算了正常海况下和极端海况下托管架疲劳损伤度并对疲劳寿命进行了评估。研究发现托管架在正常海况下作业符合安全要求,在极端海况下局部结构会受到破坏。并从托管架结构安全监测角度,筛选了结构疲劳分析关键点位,为监测点位的选取提供了依据。  相似文献   

极地冰钻关键技术研究进展          下载免费PDF全文

张楠  王亮  Pavel Talalay  范晓鹏  王如生  杨阳  洪嘉琳  宫达  孙友宏  李院生  李冰 《探矿工程》2020,47(2):1-16

极地冰钻技术是获取冰芯，研究冰盖-冰架-海洋相互作用，以及获取极地冰下基岩与冰下水环境样品，开展冰下环境探测的重要手段。目前极地冰钻技术的难点与前沿主要包括深冰芯钻探、冰架热水钻、冰下基岩钻和冰下水环境采样与观测技术。本文针对以上4个极地冰钻关键技术，对国内外相关技术的研究进展与项目开展情况进行了总结与梳理。综合来看，虽然我国开展极地钻探技术研究起步较晚，但随着我国极地战略不断推进，我国的极地冰钻关键技术与装备的研究正持续向着赶超极地钻探强国方向迈进，这必将为我国的极地科学研究提供强有力的技术支撑。  相似文献   

基于YOLOv3深度学习的海雾气象条件下海上船只实时检测     

王飞  刘梦婷  刘雪芹  秦志亮  马本俊  郑毅 《海洋科学》2020,44(8):197-204

海雾气象条件下船只高精度检测识别面临较大困难，传统的目标识别、定位方法效果差强人意。作者围绕海雾气象条件下不同类型船只的实时检测问题，提出一种基于YOLOv3深度学习的实时海上船只检测新思路。首先构建清晰图片和模糊图片（海雾、雨）的判别方法，实现图片清晰度分类处理；其次为提高海雾气象条件下海上船只的实时检测精度，消除海雾遮挡对目标识别的影响，运用暗通道先验去雾方法对含有海雾的图像实行去雾；最后基于YOLOv3深度学习算法对精细处理后的图像进行船只实时检测。实验结果表明该方法能够在海雾气象条件下高效、准确地检测到船只，对海上复杂环境条件下的船只实时检测研究具有一定的理论指导意义。  相似文献   

星站差分与PPP技术在深远海调查中的位置服务精度分析     

周东旭  唐秋华  张化疑  梁冠辉  厉峰 《海洋通报》2020,39(2):215-222

利用在全球不同海域的船载GNSS进出港数据,以事后动态处理技术(PPK)的坐标计算值为评价基准,分析了Veripos星站差分系统和事后动态精密单点定位技术(PPP)在不同运动状态下的位置服务精度。结果表明,Veripos与PPP在低动态下的平面与高程位置服务精度可优于6.2 cm和14.9 cm,在常规动态下平均精度优于20 cm;PPP与Veripos坐标分量平均互差小于15 cm,标准差小于23 cm,在深远海调查中PPP技术可作为星站差分系统的有效补充和特殊情况下的位置服务替代。  相似文献   

基于ABAQUS的深水连接器连接性能分析     

曹博  蔡志杰  石中玉  张玉龙  段梦兰 《海洋工程》2020,38(3):132-139

为解决现有深水连接器连接性能研究中力学分析建模不准确,且缺乏抗弯抗扭能力分析的问题,基于ABAQUS有限元分析软件对深水连接器进行三维模型动态仿真分析,对连接器的受力、密封性能以及在实际工程需求中不同内压下的抗弯及抗扭性能进行深入研究。结果表明:在安装及生产两种工况下,深水连接器各部件除密封环外受力均满足其强度设计要求,密封环接触表面发生合理塑性变形,满足密封要求;随着内压的增加,深水连接器的抗弯能力逐渐下降,抗扭能力则呈现增加的趋势;极限弯矩分别在0 MPa与35 MPa内压下的判定依据为密封失效,在14 MPa与52 MPa内压下的判定依据为下毂座屈服,而极限扭矩在不同内压下的判定依据均为密封失效。  相似文献   

Water mining from the deep critical zone by apple trees growing on loess     

Huijie Li  Bingcheng Si  Pute Wu  Jeffrey J. McDonnell 《水文研究》2019,33(2):320-327

There have been significant recent advances in understanding the ecohydrology of deep soil. However, the links between root development and water usage in the deep critical zone remains poorly understood. To clarify the interaction between water use and root development in deep soil, we investigated soil water and root profiles beyond maximum rooting depth in five apple orchards planted on farmland with stand ages of 8, 11, 15, 18, and 22 years in a subhumid region on the Chinese Loess Plateau. Apple trees rooted progressively deeper for water with increasing stand age and reached 23.2 ± 0.8 m for the 22‐year‐old trees. Soil water deficit in deep soil increased with tree age and was 1,530 ± 43 mm for a stand age of 22 years. Measured root deepening rate was far great than the reported pore water velocity, which demonstrated that trees are mining resident old water. The deficits are not replenished during the life‐span of the orchard, showing a one‐way mining of the critical zone water. The one‐way root water mining may have changed the fine root profile from an exponential pattern in the 8‐year‐old orchard to a relative uniform distribution in older orchards. Our findings enhance our understanding of water‐root interaction in deep soil and reveal the unintended consequences of critical zone dewatering during the lifespan of apple trees.  相似文献   

Macrobenthic infaunal communities associated with deep‐sea hydrocarbon seeps in the northern Gulf of Mexico          下载免费PDF全文

Travis W. Washburn  Amanda W. J. Demopoulos  Paul A. Montagna 《Marine Ecology》2018,39(3)

There are thousands of seeps in the deep ocean worldwide; however, many questions remain about their contributions to global biodiversity and the surrounding deep‐sea environment. In addition to being globally distributed, seeps provide several benefits to humans such as unique habitats, organisms with novel genes, and carbon regulation. The purpose of this study is to determine whether there are unique seep macrobenthic assemblages, by comparing seep and nonseep environments, different seep habitats, and seeps at different depths and locations. Infaunal community composition, diversity, and abundance were examined between seep and nonseep background environments and among three seep habitats (i.e., microbial mats, tubeworms, and soft‐bottom seeps). Abundances were higher at seep sites compared to background areas. Abundance and diversity also differed among microbial mat, tubeworm, and soft‐bottom seep habitats. Although seeps contained different macrobenthic assemblages than nonseep areas, infaunal communities were also generally unique for each seep. Variability was 75% greater within communities near seeps compared to communities in background areas. Thus, high variability in community structure characterized seep communities rather than specific taxa. The lack of similarity among seep sites supports the idea that there are no specific infauna that can be used as indicators of seepage throughout the northern Gulf of Mexico, at least at higher taxonomic levels.  相似文献   

基于深度残差网络的机载LiDAR点云分类     

赵传  郭海涛  卢俊  余东行  张保明 《测绘学报》2020,49(2):202-213

机载LiDAR点云的分类是利用其进行城市场景三维重建的关键步骤之一。为充分利用现有的图像领域性能较好的深度学习网络模型,提高点云分类精度,并降低训练时间和对训练样本数量的要求,本文提出一种基于深度残差网络的机载LiDAR点云分类方法。首先提取归一化高程、表面变化率、强度和归一化植被指数4种具有较高区分度的点云低层次特征;然后通过设置不同的邻域大小和视角,利用所提出的点云特征图生成策略,得到多尺度和多视角点云特征图;再将点云特征图输入到预训练的深度残差网络,提取多尺度和多视角深层次特征;最后构建并训练神经网络分类器,利用训练的模型对待分类点云进行预测,经后处理得到分类结果。利用ISPRS三维语义标记竞赛的公开标准数据集进行试验,结果表明,本文方法可有效区分建筑物、地面、车辆等8类地物,分类结果的总体精度为87.1%,可为城市场景三维重建提供可靠的信息。  相似文献